Abstract
Over the past few decades, advancements in computing technologies have propelled research in Human-Computer Interaction (HCI). Recently, the rise of artificial intelligence, particularly deep learning and pre-trained models like BERT and GPT, has revolutionized Natural Language Processing (NLP), making HCI applications more intelligent and personalized. NLP has emerged as a critical technology in enhancing HCI, enabling more intuitive and efficient communication between users and machines. This review explores the various applications of NLP in HCI, highlighting its significant role in user interface design, chatbots, and virtual assistants. Specifically, the paper examines how NLP techniques such as intent recognition, sentiment analysis, and language generation contribute to the creation of more responsive and user-friendly interfaces through voice input, personalized experiences, and optimized feedback mechanisms. Furthermore, the challenges and limitations of implementing NLP in HCI are discussed, particularly concerning data privacy, model effectiveness, and the ethical implications of deploying NLP systems, with a focus on privacy and trustworthiness. Finally, the paper considers future research directions in this field, emphasizing the importance of interdisciplinary collaboration in overcoming current barriers and enhancing the applicability of NLP in real-world contexts, while urging developers to prioritize responsible AI practices in their designs.
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